Tag Archives: storm

Who will win the 2019 NRL Premiership?

At this time of year, is there anything else you want to know more than the answer to this question?

For our crystal ball, we turn to Monte Carlo simulations. These simulations work on the principle that if we know the inputs to a complex system and how they relate to each other, then we can test the outcomes of that system using random numbers to simulate different situations.

At its most basic, just imagine if you simulated the outcome of football matches by rolling dice. Numbers one and two might represent a win for the Gold Coast and numbers three through six might be a win for Wests. If you repeat that a couple of thousand times, not only will you be extremely bored but the Gold Coast will “win” about 33% of the time and Wests 66%.

Now take the same approach for the nine finals games, with the winner advancing per the NRL’s system, but instead of using dice, you generate a random number between zero and one and calculate the win probability using Archimedes (form) Elo ratings. Then repeat it 5,000 times over. The number of times that the Storm or Roosters or Broncos or Eels “win” the premiership across your simulations should give you some insight into the probability of that happening in real life. I call this the Finals Stocky and I present its findings.

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A deep dive for each team’s 2019 NRL season

With the first Maori versus Indigenous All-stars game and another edition of the World Club Challenge in the history books, our attention turns to the NRL season ahead.

As with last year, I’m going to do a SWOP – Strength, Weakness, Opportunity and Prospect – analysis for each team. My general philosophy for judging a team’s prospects is that where a team finishes on the ladder the previous year is a more or less accurate reflection of their level, give or take a win or two. If no changes are made, we should see a similar performance if the season was repeated. There are exceptions, e.g. the Raiders pathological inability to close out a game should be relatively easy to fix and the Knights’ managed maybe two convincing wins in 2018 but still finished eleventh, but broadly, if a team finishes with seven wins and they hope to improve to thirteen and make the finals, then we should look at what significant changes have been made in order to make that leap up the table.

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One thing new NRL fans need to know about each team

Last year’s Rugby League World Cup introduced the sport to a lot of new potential fans around the world. If anyone in rugby league administration could see past their nose, they’d be trying to win over these new converts to the game’s top competition: the National Rugby League.

The 2018 season starts this week and if you’re new to the sport, trying to navigate the franchises and understanding why nine teams are based in Sydney can be an arduous task, doubly so if you’re American. I’m here to help by giving you a small overview of each team, just like you guys did for us.

If you need a wider perspective, check out the Complete History of the NRL and the Complete History of the NRL (nerd edition).

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A deep dive for each NRL team’s 2018 season

The only thing more reliable than March bringing rugby league back is the slew of season previews that each and every media outlet feels the need to produce. I’m no different in this regard and here is what is likely to be the longest post I’ve ever compiled.

This year’s season preview takes a look at each team and is a mix of my usual statistics, a bit of SWOT analysis and some good old fashioned taking a wild punt and hoping it’ll make you look wise come October.

(A SWOT analysis is where you look at Strengths, Weaknesses, Opportunities and Threats. There’s only one threat in the NRL, and that’s the other fifteen teams, so it’s more of a SWO analysis)

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Club Report – Melbourne Storm

mel-badgeBackground

The Melbourne Storm were founded in 1998, in the immediate aftermath of the Super League-ARL dispute. Getting a team in Melbourne was a priority for Newscorp in order to expand the footprint of the game.

Early financial concessions meant that the Storm won their first premiership in only their second season in 1999. Thereafter, more sustained success arrived, with three minor premierships in a row from 2006 to 2008, four grand finals in a row from 2006 to 2009 and two premierships in 2007 and 2009. Melbourne, and rivals Manly, were the most dominant teams of this period. It all came apart in 2010 when massive salary cap rorts were uncovered. The Storm were stripped of the minor and major premierships from the 2006 to 2009 period and lost all their competition points in 2010, ensuring the club’s only wooden spoon.

The Storm bounced back quickly, winning a legitimate minor premiership in 2011 and a premiership in 2012. Since then, they’ve kept winning with two more minor premierships in 2016 and 2017. There’s not a lot of superlatives left to describe the Storm – even their cheating was monumental and they’ve had more NRL titles stripped than most clubs have won – and the 2017 team could make an excellent case for being the best vintage produced in the last twenty years.

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Analysis – Stocky vs Reality: Did your team outperform? (Pt II)

The Stocky is the main forecasting tool driving the analysis on this site. It’s a simulator of the season ahead, using the Monte Carlo method and based on Elo ratings, that gives insight into the future performance of each club. My main interest has been the number of wins, as it determines ladder positions which in turn have a big impact on the finals. The Stocky might not be able to tell you which games a team will win, but it is good at telling you how many wins are ahead.

But how does a computer simulation (in reality, a very large spreadsheet) compare to reality? To test it, I’ve put together a graph of each team’s performance against what the Stocky projected for them. Each graph shows:

  • The Stocky’s projection for total wins (blue)
  • Converting that projection to a “pace” for that point in the season (red)
  • Comparing that to the actual number of wins (yellow)

It will never be exactly right, particularly as you can only ever win whole numbers of games and the Stocky loves a decimal point, but as we’ll see, the Stocky is not too bad at tracking form and projecting that forward.

This week is Part II, from North Queensland to Wests Tigers. Part I, from Brisbane to Newcastle, was last week. Also see this week’s projections update for some errors in the Stocky.

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Analysis – Stocky vs Reality: Did your team outperform? (Pt I)

The Stocky is the main forecasting tool driving the analysis on this site. It’s a simulator of the season ahead, using the Monte Carlo method and based on Elo ratings, that gives insight into the future performance of each club. My main interest has been the number of wins, as it determines ladder positions which in turn have a big impact on the finals. The Stocky might not be able to tell you which games a team will win, but it is good at telling you how many wins are ahead.

But how does a computer simulation (in reality, a very large spreadsheet) compare to reality? To test it, I’ve put together a graph of each team’s performance against what the Stocky projected for them. Each graph shows:

  • The Stocky’s projection for total wins (blue)
  • Converting that projection to a “pace” for that point in the season (red)
  • Comparing that to the actual number of wins (yellow)

It will never be exactly right, particularly as you can only ever win whole numbers of games and the Stocky loves a decimal point, but as we’ll see, the Stocky is not too bad at tracking form and projecting that forward.

This week is Part I, from Brisbane to Newcastle. Part II, from North Queensland to Wests Tigers, will be next week.

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